ArticleReproductive sciences (Thousand Oaks, Calif.)2023
LncRNA-LA16c-313D11.11,A Signature to Predict Endometrial Carcinoma Patients with a Better Survival.
Article in Reproductive sciences (Thousand Oaks, Calif.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
- A Machine Learning Approach to Build and Evaluate a Molecular Prognostic Model for Endometrial Cancer Based on Tumour Microenvironment.Journal of cellular and molecular medicine · 2025Article
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Authors and funding
5 authors.
Funding
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Abstract
The aim of this study was to develop and internally validate a nomogram of the probability EC patients surviving longer than 5 years. Quantitative real-time PCR (qRT-PCR) was implemented to analyze the expression of lncRNA-LA16c-313D11.11 in 60 EC tissues. The clinicopathological characteristics and follow-up data were retrospectively gathered and analyzed. To establish the prediction model, multivariate logistic regression analysis was applied, and the discrimination, calibration, and clinical practicability of the prediction model were assessed with a concordance index (C-index), calibration chart, and decision curve analysis. Bootstrap validation was performed for internal validation. The prediction factors included the age of patients, myometrial invasion, lymphovascular space invasion, histological subtype, and the expression of lncRNA-LA16C-313D11.11. The model demonstrated good calibration and modest discrimination (C-index = 0.860, 95% confidence interval: 0.724-0.946). Moreover, the interval validation achieved a high C-index value of 0.778. This study revealed the predictive value of lncRNA-LA16C-313D11.11 and successfully developed a nomogram for predicting EC patients survival longer than 5 years, which may facilitate the institution of personalized treatment algorithms, surveillance strategies, and lifestyle interventions.
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Registered trials
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